Diabetes and Cardiovascular Disease Interventions by Community Pharmacists: A Systematic Review
Notice bibliographique
Résumé
OBJECTIVE: To systematically review and assess the quality of studies evaluating community pharmacist interventions for preventing or managing diabetes or cardiovascular disease (CVD) and/or their major risk factors. DATA SOURCES: A comprehensive literature search was performed using MEDLINE (1950-February 2011), EMBASE (1980-February 2011), International Pharmaceutical Abstracts (1970-February 2011), Cumulative Index to Nursing and Allied Health Literature (1982-June 2007), and Cochrane Central Register of Controlled Trials (1898-February 2011). Search terms included: community pharmacy(ies), community pharmacist(s), cardiovascular, diabetes, and intervention. The grey literature was searched using the ProQuest Dissertations and Theses, Theses Canada, and OAlster databases. STUDY SELECTION AND DATA EXTRACTION: Articles published in English or French with all study designs were considered for the review. Studies were included if they contained interventions designed to reduce the incidence, risk, or mortality of CVD or diabetes; affect clinical indicators of CVD or diabetes mellitus (including hypertension, dyslipidemia, or hemoglobin A(1c)); and/or improve adherence to treatment strategies. Only studies involving interventions carried out primarily by pharmacists in community pharmacy settings were included. Study quality was assessed using a checklist validated for both randomized and nonrandomized studies. DATA SYNTHESIS: A total of 4142 studies were initially identified, with 40 meeting our inclusion criteria. Eleven studies were randomized controlled trials, 4 were cluster randomized trials, and 2 studies had randomized before-after designs. The remaining studies were controlled before-after (n = 2), cohort (n = 4), and uncontrolled before-after (n = 17) designs. Interventions focused on diabetes (n = 12), hypertension (n = 9), medication adherence (n = 9), lipids (n = 5), evidence-based medication initiation or optimization (n = 3), risk factor prediction scores (n = 1), and body mass index (n = 1). All studies contained interventions focused at the patient level and the majority of studies (34/40) involved interventions directed at both the physician and patient. No specific intervention emerged as superior, and study quality was generally poor, making it difficult to determine the true effect of the interventions. CONCLUSIONS: Poor study quality, time-intensive interventions, and unproven clinical significance warrant the need for further high-quality studies of community pharmacist interventions for preventing or managing diabetes or CVD and/or their major risk factors.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».